Abstract
Data mining technology has attracted much attention in recent years and has shown extremely important and extensive prospects for application in the rapidly developing era of big data. According to the broad explanation given in Han et al. (Data Mining-Concepts and Techniques (3rd Edition), Morgan Kaufmann, 2012), data mining refers to the process of mining interesting patterns and knowledge from a large amount of data. The data sources include databases, data warehouses, the web, and other information repositories or data flowing into the system dynamically. Since this technology was originally proposed for the discovery and extraction of useful knowledge from databases, the term is usually written as knowledge discovery in databases (KDD).
This book introduces the methods and techniques of interest to users for mining patterns and knowledge from natural language texts. This technique is called text data mining, sometimes abbreviated as text mining. The text referred to here includes common TXT files, doc/docx files, PDF files, HTML files, and any other format of data file with language text as the main content.
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Zong, C., Xia, R., Zhang, J. (2021). Introduction. In: Text Data Mining. Springer, Singapore. https://doi.org/10.1007/978-981-16-0100-2_1
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DOI: https://doi.org/10.1007/978-981-16-0100-2_1
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